Typically, an ultrasound system enables a body that is to be examined of an examination subject, in particular a human patient, to be examined non-invasively. An ultrasound system for medical diagnostics typically comprises an ultrasound probe which is placed onto a body surface of the patient by a physician and, in close contact with the skin of the patient, generates an ultrasound image. For this purpose, the ultrasound probe contains a one-dimensional or two-dimensional piezoelectric array in which electrical transmit pulses are converted into pressure pulses at a specific frequency or in a specific frequency band or, as the case may be, pressure pulses are converted into electrical receive signals. Normally, ultrasound images can be generated from the electrical receive signals, the ultrasound images usually being visualized in a specific mode.
Typically, the ultrasound probe is moved during an ultrasound examination. A method is described in U.S. Pat. No. 9,420,997 B2 in which motion artifacts may be suppressed in ultrasound diagnostic imaging.
A combination of a robot arm with an ultrasound probe is disclosed in WO 2017 020 081 A1.
Artificial neural networks have been a focus of attention in science and industry for some considerable time already. Artificial neural networks are modeled on the natural neural networks which are formed by nerve cell interconnections in the brain and spinal cord. An artificial neural network typically comprises a plurality of nodes and connections between nodes. In a training phase, the neural network is able to learn based on changes that are made to weightings of the connections. Typically, artificial neural networks deliver better results in challenging applications than competing machine learning methods.
DE 10 2015 212 953 A1 describes a possible application of a trained artificial neural network.